Volunteer Summary

CONSORT Flow Diagram

Overall status

Characteristic

Overall1

Control1

Treatment1

time_point

1st

76

39

37

2nd

60

33

27

1n

Demographic information

Characteristic

N

Overall, N = 761

control, N = 391

treatment, N = 371

p-value2

age

76

41.40 ± 18.51 (21 - 148)

42.47 ± 21.27 (22 - 148)

40.26 ± 15.28 (21 - 70)

0.605

gender

76

0.085

female

57 (75%)

26 (67%)

31 (84%)

male

19 (25%)

13 (33%)

6 (16%)

occupation

76

0.865

civil

3 (3.9%)

2 (5.1%)

1 (2.7%)

clerk

15 (20%)

7 (18%)

8 (22%)

homemaker

7 (9.2%)

2 (5.1%)

5 (14%)

manager

10 (13%)

6 (15%)

4 (11%)

other

9 (12%)

4 (10%)

5 (14%)

professional

11 (14%)

8 (21%)

3 (8.1%)

retired

3 (3.9%)

1 (2.6%)

2 (5.4%)

service

4 (5.3%)

2 (5.1%)

2 (5.4%)

student

12 (16%)

6 (15%)

6 (16%)

unemploy

2 (2.6%)

1 (2.6%)

1 (2.7%)

working_status

76

52 (68%)

29 (74%)

23 (62%)

0.253

marital

76

>0.999

divorced

3 (3.9%)

1 (2.6%)

2 (5.4%)

married

21 (28%)

11 (28%)

10 (27%)

single

51 (67%)

26 (67%)

25 (68%)

widowed

1 (1.3%)

1 (2.6%)

0 (0%)

marital_r

76

>0.999

married

21 (28%)

11 (28%)

10 (27%)

other

4 (5.3%)

2 (5.1%)

2 (5.4%)

single

51 (67%)

26 (67%)

25 (68%)

education

76

0.034

primary

0 (0%)

0 (0%)

0 (0%)

secondary

11 (14%)

2 (5.1%)

9 (24%)

post-secondary

13 (17%)

9 (23%)

4 (11%)

university

52 (68%)

28 (72%)

24 (65%)

university_edu

76

52 (68%)

28 (72%)

24 (65%)

0.516

family_income

76

0.518

0_10000

9 (12%)

4 (10%)

5 (14%)

10001_20000

15 (20%)

5 (13%)

10 (27%)

20001_30000

13 (17%)

8 (21%)

5 (14%)

30001_40000

10 (13%)

5 (13%)

5 (14%)

40000_above

29 (38%)

17 (44%)

12 (32%)

high_income

76

39 (51%)

22 (56%)

17 (46%)

0.362

religion

76

0.524

buddhism

5 (6.6%)

4 (10%)

1 (2.7%)

catholic

5 (6.6%)

2 (5.1%)

3 (8.1%)

christianity

26 (34%)

12 (31%)

14 (38%)

nil

38 (50%)

21 (54%)

17 (46%)

other

1 (1.3%)

0 (0%)

1 (2.7%)

taoism

1 (1.3%)

0 (0%)

1 (2.7%)

religion_r

76

0.699

christianity

31 (41%)

14 (36%)

17 (46%)

nil

38 (50%)

21 (54%)

17 (46%)

other

7 (9.2%)

4 (10%)

3 (8.1%)

source

76

0.012

bokss

34 (45%)

14 (36%)

20 (54%)

facebook

12 (16%)

10 (26%)

2 (5.4%)

instagram

5 (6.6%)

5 (13%)

0 (0%)

other

11 (14%)

4 (10%)

7 (19%)

refresh

14 (18%)

6 (15%)

8 (22%)

1Mean ± SD (Range); n (%)

2Two Sample t-test; Pearson's Chi-squared test; Fisher's exact test

Measurement

Characteristic

N

Overall, N = 761

control, N = 391

treatment, N = 371

p-value2

sets

76

19.49 ± 2.22 (15 - 25)

19.18 ± 2.14 (15 - 24)

19.81 ± 2.30 (15 - 25)

0.218

setv

76

11.16 ± 1.67 (8 - 15)

11.03 ± 1.63 (8 - 14)

11.30 ± 1.71 (8 - 15)

0.481

maks

76

44.67 ± 3.71 (36 - 54)

44.26 ± 3.65 (36 - 52)

45.11 ± 3.77 (38 - 54)

0.321

ibs

76

15.58 ± 2.19 (9 - 20)

15.62 ± 2.14 (11 - 20)

15.54 ± 2.28 (9 - 20)

0.883

ers_e

76

12.28 ± 1.40 (9 - 15)

12.33 ± 1.46 (9 - 15)

12.22 ± 1.36 (9 - 15)

0.718

ers_r

76

11.34 ± 1.46 (8 - 15)

11.33 ± 1.36 (8 - 14)

11.35 ± 1.57 (8 - 15)

0.957

pss_pa

76

44.93 ± 4.60 (30 - 54)

44.41 ± 4.59 (30 - 54)

45.49 ± 4.60 (31 - 54)

0.311

pss_ps

76

25.37 ± 7.39 (12 - 42)

26.51 ± 7.71 (14 - 42)

24.16 ± 6.92 (12 - 41)

0.167

pss

76

43.43 ± 11.26 (21 - 72)

45.10 ± 11.69 (23 - 72)

41.68 ± 10.65 (21 - 67)

0.186

rki_responsible

76

21.29 ± 3.93 (13 - 29)

20.82 ± 4.25 (13 - 29)

21.78 ± 3.54 (14 - 28)

0.288

rki_nonlinear

76

13.45 ± 2.77 (7 - 22)

13.21 ± 2.48 (7 - 20)

13.70 ± 3.06 (8 - 22)

0.438

rki_peer

76

20.47 ± 2.22 (16 - 25)

20.54 ± 2.22 (16 - 25)

20.41 ± 2.24 (16 - 25)

0.796

rki_expect

76

4.66 ± 0.99 (3 - 7)

4.46 ± 0.94 (3 - 6)

4.86 ± 1.00 (3 - 7)

0.075

rki

76

59.87 ± 5.89 (50 - 80)

59.03 ± 5.89 (50 - 76)

60.76 ± 5.83 (50 - 80)

0.202

raq_possible

76

15.55 ± 1.91 (12 - 20)

15.64 ± 2.03 (12 - 20)

15.46 ± 1.79 (12 - 20)

0.681

raq_difficulty

76

12.34 ± 1.45 (9 - 15)

12.44 ± 1.48 (9 - 15)

12.24 ± 1.42 (9 - 15)

0.565

raq

76

27.89 ± 3.10 (21 - 35)

28.08 ± 3.26 (21 - 35)

27.70 ± 2.95 (21 - 35)

0.602

who

76

15.05 ± 4.36 (7 - 25)

14.95 ± 4.29 (8 - 25)

15.16 ± 4.49 (7 - 25)

0.833

phq

76

3.46 ± 3.66 (0 - 18)

3.72 ± 3.68 (0 - 14)

3.19 ± 3.66 (0 - 18)

0.532

gad

76

3.12 ± 3.13 (0 - 12)

3.28 ± 3.14 (0 - 12)

2.95 ± 3.16 (0 - 12)

0.643

nb_pcs

76

50.60 ± 7.88 (25 - 63)

51.43 ± 7.63 (25 - 63)

49.72 ± 8.14 (27 - 61)

0.349

nb_mcs

76

50.94 ± 8.78 (22 - 70)

50.39 ± 9.06 (22 - 68)

51.52 ± 8.57 (35 - 70)

0.578

1Mean ± SD (Range)

2Two Sample t-test

Data analysis

Table

Group

Characteristic

Beta

SE1

95% CI1

p-value

sets

(Intercept)

19.2

0.332

18.5, 19.8

group

control

—

—

—

treatment

0.631

0.476

-0.301, 1.56

0.187

time_point

1st

—

—

—

2nd

-0.321

0.401

-1.11, 0.465

0.426

group * time_point

treatment * 2nd

0.053

0.591

-1.11, 1.21

0.928

Pseudo R square

0.030

setv

(Intercept)

11.0

0.268

10.5, 11.6

group

control

—

—

—

treatment

0.272

0.384

-0.481, 1.02

0.481

time_point

1st

—

—

—

2nd

0.253

0.272

-0.281, 0.787

0.356

group * time_point

treatment * 2nd

-0.132

0.403

-0.922, 0.658

0.744

Pseudo R square

0.007

maks

(Intercept)

44.3

0.627

43.0, 45.5

group

control

—

—

—

treatment

0.852

0.898

-0.909, 2.61

0.346

time_point

1st

—

—

—

2nd

0.043

0.502

-0.940, 1.03

0.932

group * time_point

treatment * 2nd

0.388

0.744

-1.07, 1.85

0.604

Pseudo R square

0.018

ibs

(Intercept)

15.6

0.335

15.0, 16.3

group

control

—

—

—

treatment

-0.075

0.480

-1.02, 0.867

0.876

time_point

1st

—

—

—

2nd

0.190

0.322

-0.441, 0.821

0.557

group * time_point

treatment * 2nd

0.319

0.477

-0.616, 1.25

0.506

Pseudo R square

0.008

ers_e

(Intercept)

12.3

0.226

11.9, 12.8

group

control

—

—

—

treatment

-0.117

0.324

-0.752, 0.518

0.718

time_point

1st

—

—

—

2nd

-0.524

0.188

-0.894, -0.155

0.007

group * time_point

treatment * 2nd

0.537

0.280

-0.011, 1.09

0.059

Pseudo R square

0.020

ers_r

(Intercept)

11.3

0.230

10.9, 11.8

group

control

—

—

—

treatment

0.018

0.330

-0.628, 0.664

0.956

time_point

1st

—

—

—

2nd

-0.155

0.257

-0.658, 0.349

0.549

group * time_point

treatment * 2nd

0.363

0.379

-0.380, 1.11

0.342

Pseudo R square

0.008

pss_pa

(Intercept)

44.4

0.725

43.0, 45.8

group

control

—

—

—

treatment

1.08

1.040

-0.962, 3.11

0.303

time_point

1st

—

—

—

2nd

-1.29

0.804

-2.87, 0.283

0.113

group * time_point

treatment * 2nd

0.028

1.188

-2.30, 2.36

0.981

Pseudo R square

0.034

pss_ps

(Intercept)

26.5

1.175

24.2, 28.8

group

control

—

—

—

treatment

-2.35

1.684

-5.65, 0.951

0.166

time_point

1st

—

—

—

2nd

1.16

1.135

-1.07, 3.38

0.312

group * time_point

treatment * 2nd

-1.16

1.681

-4.46, 2.13

0.491

Pseudo R square

0.040

pss

(Intercept)

45.1

1.750

41.7, 48.5

group

control

—

—

—

treatment

-3.43

2.509

-8.34, 1.49

0.175

time_point

1st

—

—

—

2nd

2.46

1.651

-0.772, 5.70

0.141

group * time_point

treatment * 2nd

-1.22

2.445

-6.01, 3.58

0.621

Pseudo R square

0.041

rki_responsible

(Intercept)

20.8

0.587

19.7, 22.0

group

control

—

—

—

treatment

0.963

0.841

-0.685, 2.61

0.255

time_point

1st

—

—

—

2nd

0.026

0.615

-1.18, 1.23

0.966

group * time_point

treatment * 2nd

-0.415

0.910

-2.20, 1.37

0.650

Pseudo R square

0.013

rki_nonlinear

(Intercept)

13.2

0.458

12.3, 14.1

group

control

—

—

—

treatment

0.498

0.657

-0.790, 1.79

0.451

time_point

1st

—

—

—

2nd

-0.314

0.445

-1.19, 0.558

0.483

group * time_point

treatment * 2nd

0.496

0.659

-0.796, 1.79

0.455

Pseudo R square

0.018

rki_peer

(Intercept)

20.5

0.364

19.8, 21.3

group

control

—

—

—

treatment

-0.133

0.521

-1.15, 0.888

0.799

time_point

1st

—

—

—

2nd

0.020

0.365

-0.696, 0.736

0.956

group * time_point

treatment * 2nd

0.155

0.540

-0.904, 1.21

0.775

Pseudo R square

0.001

rki_expect

(Intercept)

4.46

0.153

4.16, 4.76

group

control

—

—

—

treatment

0.403

0.220

-0.028, 0.834

0.069

time_point

1st

—

—

—

2nd

0.177

0.197

-0.210, 0.563

0.374

group * time_point

treatment * 2nd

0.026

0.290

-0.543, 0.596

0.928

Pseudo R square

0.052

rki

(Intercept)

59.0

0.885

57.3, 60.8

group

control

—

—

—

treatment

1.73

1.268

-0.754, 4.22

0.175

time_point

1st

—

—

—

2nd

-0.103

0.920

-1.91, 1.70

0.911

group * time_point

treatment * 2nd

0.231

1.361

-2.44, 2.90

0.866

Pseudo R square

0.027

raq_possible

(Intercept)

15.6

0.293

15.1, 16.2

group

control

—

—

—

treatment

-0.182

0.419

-1.00, 0.641

0.666

time_point

1st

—

—

—

2nd

-0.307

0.313

-0.921, 0.307

0.331

group * time_point

treatment * 2nd

0.687

0.463

-0.220, 1.59

0.143

Pseudo R square

0.010

raq_difficulty

(Intercept)

12.4

0.232

12.0, 12.9

group

control

—

—

—

treatment

-0.193

0.333

-0.845, 0.459

0.564

time_point

1st

—

—

—

2nd

-0.017

0.222

-0.453, 0.419

0.940

group * time_point

treatment * 2nd

0.186

0.329

-0.459, 0.831

0.574

Pseudo R square

0.003

raq

(Intercept)

28.1

0.489

27.1, 29.0

group

control

—

—

—

treatment

-0.374

0.701

-1.75, 0.999

0.594

time_point

1st

—

—

—

2nd

-0.286

0.469

-1.20, 0.633

0.544

group * time_point

treatment * 2nd

0.864

0.694

-0.497, 2.22

0.218

Pseudo R square

0.005

who

(Intercept)

14.9

0.696

13.6, 16.3

group

control

—

—

—

treatment

0.213

0.997

-1.74, 2.17

0.831

time_point

1st

—

—

—

2nd

-0.232

0.570

-1.35, 0.884

0.685

group * time_point

treatment * 2nd

-0.072

0.845

-1.73, 1.58

0.933

Pseudo R square

0.001

phq

(Intercept)

3.72

0.558

2.62, 4.81

group

control

—

—

—

treatment

-0.529

0.800

-2.10, 1.04

0.510

time_point

1st

—

—

—

2nd

0.021

0.386

-0.735, 0.778

0.956

group * time_point

treatment * 2nd

0.023

0.573

-1.10, 1.15

0.968

Pseudo R square

0.006

gad

(Intercept)

3.28

0.511

2.28, 4.28

group

control

—

—

—

treatment

-0.336

0.732

-1.77, 1.10

0.647

time_point

1st

—

—

—

2nd

0.166

0.424

-0.664, 0.996

0.696

group * time_point

treatment * 2nd

0.154

0.628

-1.08, 1.39

0.807

Pseudo R square

0.003

nb_pcs

(Intercept)

51.4

1.208

49.1, 53.8

group

control

—

—

—

treatment

-1.71

1.731

-5.10, 1.69

0.327

time_point

1st

—

—

—

2nd

-0.539

0.896

-2.30, 1.22

0.549

group * time_point

treatment * 2nd

2.38

1.331

-0.227, 4.99

0.078

Pseudo R square

0.010

nb_mcs

(Intercept)

50.4

1.358

47.7, 53.1

group

control

—

—

—

treatment

1.13

1.946

-2.68, 4.95

0.562

time_point

1st

—

—

—

2nd

-0.178

1.256

-2.64, 2.28

0.888

group * time_point

treatment * 2nd

-0.776

1.861

-4.42, 2.87

0.678

Pseudo R square

0.004

1SE = Standard Error, CI = Confidence Interval

Text

sets

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sets with group and time_point (formula: sets ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.37) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 19.18 (95% CI [18.53, 19.83], t(130) = 57.79, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.63, 95% CI [-0.30, 1.56], t(130) = 1.33, p = 0.184; Std. beta = 0.30, 95% CI [-0.14, 0.75])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.32, 95% CI [-1.11, 0.46], t(130) = -0.80, p = 0.423; Std. beta = -0.15, 95% CI [-0.53, 0.22])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.05, 95% CI [-1.11, 1.21], t(130) = 0.09, p = 0.928; Std. beta = 0.03, 95% CI [-0.53, 0.58])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

setv

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict setv with group and time_point (formula: setv ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.55) and the part related to the fixed effects alone (marginal R2) is of 7.41e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.03 (95% CI [10.50, 11.55], t(130) = 41.13, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.27, 95% CI [-0.48, 1.02], t(130) = 0.71, p = 0.480; Std. beta = 0.16, 95% CI [-0.29, 0.62])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.25, 95% CI [-0.28, 0.79], t(130) = 0.93, p = 0.353; Std. beta = 0.15, 95% CI [-0.17, 0.47])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.13, 95% CI [-0.92, 0.66], t(130) = -0.33, p = 0.743; Std. beta = -0.08, 95% CI [-0.55, 0.40])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

maks

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict maks with group and time_point (formula: maks ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.73) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.26 (95% CI [43.03, 45.48], t(130) = 70.61, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.85, 95% CI [-0.91, 2.61], t(130) = 0.95, p = 0.343; Std. beta = 0.22, 95% CI [-0.23, 0.67])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.04, 95% CI [-0.94, 1.03], t(130) = 0.09, p = 0.931; Std. beta = 0.01, 95% CI [-0.24, 0.26])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.39, 95% CI [-1.07, 1.85], t(130) = 0.52, p = 0.602; Std. beta = 0.10, 95% CI [-0.28, 0.48])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ibs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ibs with group and time_point (formula: ibs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 8.03e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.62 (95% CI [14.96, 16.27], t(130) = 46.59, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.07, 95% CI [-1.02, 0.87], t(130) = -0.16, p = 0.876; Std. beta = -0.04, 95% CI [-0.49, 0.42])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.19, 95% CI [-0.44, 0.82], t(130) = 0.59, p = 0.555; Std. beta = 0.09, 95% CI [-0.21, 0.40])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.32, 95% CI [-0.62, 1.25], t(130) = 0.67, p = 0.504; Std. beta = 0.15, 95% CI [-0.30, 0.61])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_e

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_e with group and time_point (formula: ers_e ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.70) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.33 (95% CI [11.89, 12.78], t(130) = 54.57, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.12, 95% CI [-0.75, 0.52], t(130) = -0.36, p = 0.718; Std. beta = -0.08, 95% CI [-0.54, 0.37])
  • The effect of time point [2nd] is statistically significant and negative (beta = -0.52, 95% CI [-0.89, -0.15], t(130) = -2.78, p = 0.005; Std. beta = -0.38, 95% CI [-0.64, -0.11])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.54, 95% CI [-0.01, 1.09], t(130) = 1.92, p = 0.055; Std. beta = 0.39, 95% CI [-7.67e-03, 0.78])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_r

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_r with group and time_point (formula: ers_r ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.45) and the part related to the fixed effects alone (marginal R2) is of 7.72e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.33 (95% CI [10.88, 11.78], t(130) = 49.29, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.02, 95% CI [-0.63, 0.66], t(130) = 0.05, p = 0.956; Std. beta = 0.01, 95% CI [-0.44, 0.47])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.15, 95% CI [-0.66, 0.35], t(130) = -0.60, p = 0.547; Std. beta = -0.11, 95% CI [-0.46, 0.25])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.36, 95% CI [-0.38, 1.11], t(130) = 0.96, p = 0.338; Std. beta = 0.26, 95% CI [-0.27, 0.78])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_pa

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_pa with group and time_point (formula: pss_pa ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.48) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.41 (95% CI [42.99, 45.83], t(130) = 61.22, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.08, 95% CI [-0.96, 3.11], t(130) = 1.04, p = 0.301; Std. beta = 0.24, 95% CI [-0.21, 0.68])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -1.29, 95% CI [-2.87, 0.28], t(130) = -1.61, p = 0.108; Std. beta = -0.28, 95% CI [-0.63, 0.06])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.03, 95% CI [-2.30, 2.36], t(130) = 0.02, p = 0.981; Std. beta = 6.09e-03, 95% CI [-0.50, 0.52])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_ps

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_ps with group and time_point (formula: pss_ps ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.61) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 26.51 (95% CI [24.21, 28.82], t(130) = 22.56, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -2.35, 95% CI [-5.65, 0.95], t(130) = -1.40, p = 0.163; Std. beta = -0.32, 95% CI [-0.76, 0.13])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 1.16, 95% CI [-1.07, 3.38], t(130) = 1.02, p = 0.308; Std. beta = 0.16, 95% CI [-0.14, 0.46])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.16, 95% CI [-4.46, 2.13], t(130) = -0.69, p = 0.489; Std. beta = -0.16, 95% CI [-0.60, 0.29])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss with group and time_point (formula: pss ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.63) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 45.10 (95% CI [41.67, 48.53], t(130) = 25.77, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -3.43, 95% CI [-8.34, 1.49], t(130) = -1.37, p = 0.172; Std. beta = -0.31, 95% CI [-0.75, 0.13])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 2.46, 95% CI [-0.77, 5.70], t(130) = 1.49, p = 0.136; Std. beta = 0.22, 95% CI [-0.07, 0.52])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.22, 95% CI [-6.01, 3.58], t(130) = -0.50, p = 0.619; Std. beta = -0.11, 95% CI [-0.54, 0.32])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_responsible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_responsible with group and time_point (formula: rki_responsible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.52) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.82 (95% CI [19.67, 21.97], t(130) = 35.49, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.96, 95% CI [-0.68, 2.61], t(130) = 1.15, p = 0.252; Std. beta = 0.27, 95% CI [-0.19, 0.73])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.03, 95% CI [-1.18, 1.23], t(130) = 0.04, p = 0.966; Std. beta = 7.29e-03, 95% CI [-0.33, 0.34])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.41, 95% CI [-2.20, 1.37], t(130) = -0.46, p = 0.648; Std. beta = -0.12, 95% CI [-0.61, 0.38])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_nonlinear

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_nonlinear with group and time_point (formula: rki_nonlinear ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.21 (95% CI [12.31, 14.10], t(130) = 28.81, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.50, 95% CI [-0.79, 1.79], t(130) = 0.76, p = 0.449; Std. beta = 0.18, 95% CI [-0.28, 0.64])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.31, 95% CI [-1.19, 0.56], t(130) = -0.71, p = 0.480; Std. beta = -0.11, 95% CI [-0.43, 0.20])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.50, 95% CI [-0.80, 1.79], t(130) = 0.75, p = 0.452; Std. beta = 0.18, 95% CI [-0.29, 0.64])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_peer

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_peer with group and time_point (formula: rki_peer ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.56) and the part related to the fixed effects alone (marginal R2) is of 9.23e-04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.54 (95% CI [19.83, 21.25], t(130) = 56.50, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.13, 95% CI [-1.15, 0.89], t(130) = -0.26, p = 0.798; Std. beta = -0.06, 95% CI [-0.51, 0.40])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.02, 95% CI [-0.70, 0.74], t(130) = 0.05, p = 0.956; Std. beta = 8.91e-03, 95% CI [-0.31, 0.33])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.15, 95% CI [-0.90, 1.21], t(130) = 0.29, p = 0.774; Std. beta = 0.07, 95% CI [-0.40, 0.54])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_expect

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_expect with group and time_point (formula: rki_expect ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.30) and the part related to the fixed effects alone (marginal R2) is of 0.05. The model’s intercept, corresponding to group = control and time_point = 1st, is at 4.46 (95% CI [4.16, 4.76], t(130) = 29.07, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.40, 95% CI [-0.03, 0.83], t(130) = 1.83, p = 0.067; Std. beta = 0.41, 95% CI [-0.03, 0.86])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.18, 95% CI [-0.21, 0.56], t(130) = 0.90, p = 0.371; Std. beta = 0.18, 95% CI [-0.22, 0.58])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.03, 95% CI [-0.54, 0.60], t(130) = 0.09, p = 0.928; Std. beta = 0.03, 95% CI [-0.56, 0.61])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki with group and time_point (formula: rki ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.54) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 59.03 (95% CI [57.29, 60.76], t(130) = 66.71, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.73, 95% CI [-0.75, 4.22], t(130) = 1.37, p = 0.172; Std. beta = 0.32, 95% CI [-0.14, 0.78])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.10, 95% CI [-1.91, 1.70], t(130) = -0.11, p = 0.911; Std. beta = -0.02, 95% CI [-0.35, 0.32])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.23, 95% CI [-2.44, 2.90], t(130) = 0.17, p = 0.865; Std. beta = 0.04, 95% CI [-0.45, 0.54])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_possible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_possible with group and time_point (formula: raq_possible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.50) and the part related to the fixed effects alone (marginal R2) is of 9.72e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.64 (95% CI [15.07, 16.21], t(130) = 53.44, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.18, 95% CI [-1.00, 0.64], t(130) = -0.43, p = 0.665; Std. beta = -0.10, 95% CI [-0.56, 0.35])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.31, 95% CI [-0.92, 0.31], t(130) = -0.98, p = 0.327; Std. beta = -0.17, 95% CI [-0.51, 0.17])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.69, 95% CI [-0.22, 1.59], t(130) = 1.48, p = 0.138; Std. beta = 0.38, 95% CI [-0.12, 0.88])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_difficulty

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_difficulty with group and time_point (formula: raq_difficulty ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 3.13e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.44 (95% CI [11.98, 12.89], t(130) = 53.59, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.19, 95% CI [-0.84, 0.46], t(130) = -0.58, p = 0.562; Std. beta = -0.13, 95% CI [-0.59, 0.32])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.02, 95% CI [-0.45, 0.42], t(130) = -0.08, p = 0.939; Std. beta = -0.01, 95% CI [-0.31, 0.29])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.19, 95% CI [-0.46, 0.83], t(130) = 0.57, p = 0.572; Std. beta = 0.13, 95% CI [-0.32, 0.58])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq with group and time_point (formula: raq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 5.27e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 28.08 (95% CI [27.12, 29.04], t(130) = 57.44, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.37, 95% CI [-1.75, 1.00], t(130) = -0.53, p = 0.593; Std. beta = -0.12, 95% CI [-0.58, 0.33])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.29, 95% CI [-1.20, 0.63], t(130) = -0.61, p = 0.542; Std. beta = -0.09, 95% CI [-0.40, 0.21])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.86, 95% CI [-0.50, 2.22], t(130) = 1.24, p = 0.213; Std. beta = 0.29, 95% CI [-0.16, 0.74])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

who

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict who with group and time_point (formula: who ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.71) and the part related to the fixed effects alone (marginal R2) is of 1.43e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.95 (95% CI [13.58, 16.31], t(130) = 21.48, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.21, 95% CI [-1.74, 2.17], t(130) = 0.21, p = 0.831; Std. beta = 0.05, 95% CI [-0.41, 0.50])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.23, 95% CI [-1.35, 0.88], t(130) = -0.41, p = 0.683; Std. beta = -0.05, 95% CI [-0.31, 0.21])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.07, 95% CI [-1.73, 1.58], t(130) = -0.08, p = 0.932; Std. beta = -0.02, 95% CI [-0.40, 0.37])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

phq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict phq with group and time_point (formula: phq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.80) and the part related to the fixed effects alone (marginal R2) is of 5.57e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.72 (95% CI [2.62, 4.81], t(130) = 6.66, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.53, 95% CI [-2.10, 1.04], t(130) = -0.66, p = 0.509; Std. beta = -0.15, 95% CI [-0.60, 0.30])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.02, 95% CI [-0.73, 0.78], t(130) = 0.06, p = 0.956; Std. beta = 6.10e-03, 95% CI [-0.21, 0.22])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.02, 95% CI [-1.10, 1.15], t(130) = 0.04, p = 0.967; Std. beta = 6.67e-03, 95% CI [-0.31, 0.33])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

gad

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict gad with group and time_point (formula: gad ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.70) and the part related to the fixed effects alone (marginal R2) is of 3.40e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.28 (95% CI [2.28, 4.28], t(130) = 6.42, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.34, 95% CI [-1.77, 1.10], t(130) = -0.46, p = 0.646; Std. beta = -0.11, 95% CI [-0.56, 0.35])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.17, 95% CI [-0.66, 1.00], t(130) = 0.39, p = 0.695; Std. beta = 0.05, 95% CI [-0.21, 0.31])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.15, 95% CI [-1.08, 1.39], t(130) = 0.25, p = 0.806; Std. beta = 0.05, 95% CI [-0.34, 0.44])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_pcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_pcs with group and time_point (formula: nb_pcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.76) and the part related to the fixed effects alone (marginal R2) is of 9.53e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 51.43 (95% CI [49.06, 53.80], t(130) = 42.58, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -1.71, 95% CI [-5.10, 1.69], t(130) = -0.99, p = 0.325; Std. beta = -0.23, 95% CI [-0.68, 0.22])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.54, 95% CI [-2.30, 1.22], t(130) = -0.60, p = 0.547; Std. beta = -0.07, 95% CI [-0.30, 0.16])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 2.38, 95% CI [-0.23, 4.99], t(130) = 1.79, p = 0.074; Std. beta = 0.32, 95% CI [-0.03, 0.66])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_mcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_mcs with group and time_point (formula: nb_mcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.63) and the part related to the fixed effects alone (marginal R2) is of 3.81e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 50.39 (95% CI [47.73, 53.05], t(130) = 37.11, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.13, 95% CI [-2.68, 4.95], t(130) = 0.58, p = 0.561; Std. beta = 0.14, 95% CI [-0.32, 0.60])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.18, 95% CI [-2.64, 2.28], t(130) = -0.14, p = 0.887; Std. beta = -0.02, 95% CI [-0.32, 0.28])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.78, 95% CI [-4.42, 2.87], t(130) = -0.42, p = 0.677; Std. beta = -0.09, 95% CI [-0.54, 0.35])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

Likelihood ratio tests

outcome

model

npar

AIC

BIC

logLik

deviance

Chisq

Df

p

sets

null

3

582.067

590.805

-288.034

576.067

sets

random

6

584.285

601.761

-286.143

572.285

3.782

3

0.286

setv

null

3

508.093

516.831

-251.046

502.093

setv

random

6

512.680

530.156

-250.340

500.680

1.412

3

0.703

maks

null

3

716.727

725.465

-355.364

710.727

maks

random

6

720.674

738.150

-354.337

708.674

2.053

3

0.561

ibs

null

3

564.826

573.564

-279.413

558.826

ibs

random

6

568.365

585.841

-278.182

556.365

2.462

3

0.482

ers_e

null

3

449.093

457.831

-221.547

443.093

ers_e

random

6

447.400

464.876

-217.700

435.400

7.694

3

0.053

ers_r

null

3

474.106

482.844

-234.053

468.106

ers_r

random

6

478.815

496.291

-233.407

466.815

1.291

3

0.731

pss_pa

null

3

790.996

799.734

-392.498

784.996

pss_pa

random

6

790.737

808.213

-389.369

778.737

6.259

3

0.100

pss_ps

null

3

908.657

917.395

-451.329

902.657

pss_ps

random

6

910.116

927.592

-449.058

898.116

4.541

3

0.209

pss

null

3

1,016.042

1,024.780

-505.021

1,010.042

pss

random

6

1,016.233

1,033.709

-502.116

1,004.233

5.810

3

0.121

rki_responsible

null

3

723.955

732.693

-358.978

717.955

rki_responsible

random

6

728.452

745.928

-358.226

716.452

1.503

3

0.681

rki_nonlinear

null

3

650.546

659.284

-322.273

644.546

rki_nonlinear

random

6

654.478

671.954

-321.239

642.478

2.068

3

0.558

rki_peer

null

3

588.740

597.478

-291.370

582.740

rki_peer

random

6

594.514

611.990

-291.257

582.514

0.226

3

0.973

rki_expect

null

3

378.907

387.645

-186.454

372.907

rki_expect

random

6

378.216

395.692

-183.108

366.216

6.691

3

0.082

rki

null

3

836.120

844.857

-415.060

830.120

rki

random

6

839.470

856.946

-413.735

827.470

2.649

3

0.449

raq_possible

null

3

537.319

546.057

-265.660

531.319

raq_possible

random

6

541.000

558.476

-264.500

529.000

2.320

3

0.509

raq_difficulty

null

3

462.766

471.504

-228.383

456.766

raq_difficulty

random

6

468.101

485.577

-228.050

456.101

0.665

3

0.881

raq

null

3

666.506

675.244

-330.253

660.506

raq

random

6

670.828

688.304

-329.414

658.828

1.677

3

0.642

who

null

3

745.911

754.649

-369.956

739.911

who

random

6

751.450

768.926

-369.725

739.450

0.462

3

0.927

phq

null

3

668.126

676.864

-331.063

662.126

phq

random

6

673.638

691.114

-330.819

661.638

0.488

3

0.921

gad

null

3

663.554

672.292

-328.777

657.554

gad

random

6

668.728

686.204

-328.364

656.728

0.826

3

0.843

nb_pcs

null

3

889.229

897.967

-441.614

883.229

nb_pcs

random

6

891.176

908.652

-439.588

879.176

4.053

3

0.256

nb_mcs

null

3

940.076

948.814

-467.038

934.076

nb_mcs

random

6

945.333

962.808

-466.666

933.333

0.743

3

0.863

Post hoc analysis text

Table

outcome

time

control

treatment

between

n

estimate

within es

n

estimate

within es

p

es

sets

1st

39

19.18 ± 2.07

37

19.81 ± 2.07

0.187

-0.378

sets

2nd

33

18.86 ± 2.06

0.192

27

19.54 ± 2.05

0.160

0.201

-0.410

setv

1st

39

11.03 ± 1.67

37

11.30 ± 1.67

0.481

-0.241

setv

2nd

33

11.28 ± 1.64

-0.225

27

11.42 ± 1.61

-0.108

0.740

-0.124

maks

1st

39

44.26 ± 3.91

37

45.11 ± 3.91

0.346

-0.413

maks

2nd

33

44.30 ± 3.76

-0.021

27

45.54 ± 3.63

-0.210

0.198

-0.602

ibs

1st

39

15.62 ± 2.09

37

15.54 ± 2.09

0.876

0.056

ibs

2nd

33

15.81 ± 2.04

-0.143

27

16.05 ± 1.99

-0.383

0.641

-0.184

ers_e

1st

39

12.33 ± 1.41

37

12.22 ± 1.41

0.718

0.151

ers_e

2nd

33

11.81 ± 1.36

0.677

27

12.23 ± 1.32

-0.017

0.228

-0.542

ers_r

1st

39

11.33 ± 1.44

37

11.35 ± 1.44

0.956

-0.017

ers_r

2nd

33

11.18 ± 1.42

0.145

27

11.56 ± 1.40

-0.196

0.299

-0.357

pss_pa

1st

39

44.41 ± 4.53

37

45.49 ± 4.53

0.303

-0.323

pss_pa

2nd

33

43.12 ± 4.46

0.387

27

44.22 ± 4.41

0.379

0.339

-0.331

pss_ps

1st

39

26.51 ± 7.34

37

24.16 ± 7.34

0.166

0.502

pss_ps

2nd

33

27.67 ± 7.15

-0.247

27

24.16 ± 7.00

0.001

0.058

0.750

pss

1st

39

45.10 ± 10.93

37

41.68 ± 10.93

0.175

0.503

pss

2nd

33

47.57 ± 10.62

-0.362

27

42.92 ± 10.38

-0.183

0.091

0.682

rki_responsible

1st

39

20.82 ± 3.66

37

21.78 ± 3.66

0.254

-0.378

rki_responsible

2nd

33

20.85 ± 3.59

-0.010

27

21.40 ± 3.54

0.153

0.554

-0.215

rki_nonlinear

1st

39

13.21 ± 2.86

37

13.70 ± 2.86

0.451

-0.271

rki_nonlinear

2nd

33

12.89 ± 2.79

0.171

27

13.88 ± 2.73

-0.099

0.168

-0.541

rki_peer

1st

39

20.54 ± 2.27

37

20.41 ± 2.27

0.799

0.088

rki_peer

2nd

33

20.56 ± 2.22

-0.013

27

20.58 ± 2.18

-0.116

0.970

-0.014

rki_expect

1st

39

4.46 ± 0.96

37

4.86 ± 0.96

0.069

-0.489

rki_expect

2nd

33

4.64 ± 0.96

-0.214

27

5.07 ± 0.95

-0.246

0.085

-0.521

rki

1st

39

59.03 ± 5.53

37

60.76 ± 5.53

0.175

-0.455

rki

2nd

33

58.92 ± 5.41

0.027

27

60.88 ± 5.33

-0.034

0.162

-0.515

raq_possible

1st

39

15.64 ± 1.83

37

15.46 ± 1.83

0.666

0.140

raq_possible

2nd

33

15.33 ± 1.80

0.236

27

15.84 ± 1.77

-0.293

0.276

-0.390

raq_difficulty

1st

39

12.44 ± 1.45

37

12.24 ± 1.45

0.564

0.210

raq_difficulty

2nd

33

12.42 ± 1.41

0.018

27

12.41 ± 1.38

-0.185

0.986

0.007

raq

1st

39

28.08 ± 3.05

37

27.70 ± 3.05

0.594

0.194

raq

2nd

33

27.79 ± 2.97

0.148

27

28.28 ± 2.91

-0.299

0.522

-0.253

who

1st

39

14.95 ± 4.35

37

15.16 ± 4.35

0.831

-0.091

who

2nd

33

14.72 ± 4.18

0.099

27

14.86 ± 4.04

0.130

0.894

-0.061

phq

1st

39

3.72 ± 3.49

37

3.19 ± 3.49

0.510

0.335

phq

2nd

33

3.74 ± 3.31

-0.014

27

3.23 ± 3.18

-0.028

0.549

0.320

gad

1st

39

3.28 ± 3.19

37

2.95 ± 3.19

0.647

0.193

gad

2nd

33

3.45 ± 3.07

-0.095

27

3.27 ± 2.97

-0.184

0.817

0.104

nb_pcs

1st

39

51.43 ± 7.54

37

49.72 ± 7.54

0.327

0.464

nb_pcs

2nd

33

50.89 ± 7.20

0.147

27

51.57 ± 6.93

-0.501

0.713

-0.184

nb_mcs

1st

39

50.39 ± 8.48

37

51.52 ± 8.48

0.562

-0.219

nb_mcs

2nd

33

50.21 ± 8.23

0.034

27

50.57 ± 8.03

0.184

0.866

-0.069

Between group

sets

1st

t(119.33) = 1.33, p = 0.187, Cohen d = -0.38, 95% CI (-0.31 to 1.57)

2st

t(127.85) = 1.29, p = 0.201, Cohen d = -0.41, 95% CI (-0.37 to 1.74)

setv

1st

t(105.25) = 0.71, p = 0.481, Cohen d = -0.24, 95% CI (-0.49 to 1.03)

2st

t(119.96) = 0.33, p = 0.740, Cohen d = -0.12, 95% CI (-0.69 to 0.97)

maks

1st

t(92.17) = 0.95, p = 0.346, Cohen d = -0.41, 95% CI (-0.93 to 2.64)

2st

t(107.13) = 1.30, p = 0.198, Cohen d = -0.60, 95% CI (-0.66 to 3.14)

ibs

1st

t(101.53) = -0.16, p = 0.876, Cohen d = 0.06, 95% CI (-1.03 to 0.88)

2st

t(116.98) = 0.47, p = 0.641, Cohen d = -0.18, 95% CI (-0.79 to 1.28)

ers_e

1st

t(93.94) = -0.36, p = 0.718, Cohen d = 0.15, 95% CI (-0.76 to 0.53)

2st

t(109.30) = 1.21, p = 0.228, Cohen d = -0.54, 95% CI (-0.27 to 1.11)

ers_r

1st

t(112.56) = 0.05, p = 0.956, Cohen d = -0.02, 95% CI (-0.63 to 0.67)

2st

t(124.61) = 1.04, p = 0.299, Cohen d = -0.36, 95% CI (-0.34 to 1.10)

pss_pa

1st

t(111.92) = 1.04, p = 0.303, Cohen d = -0.32, 95% CI (-0.98 to 3.14)

2st

t(124.26) = 0.96, p = 0.339, Cohen d = -0.33, 95% CI (-1.17 to 3.38)

pss_ps

1st

t(101.86) = -1.40, p = 0.166, Cohen d = 0.50, 95% CI (-5.69 to 0.99)

2st

t(117.27) = -1.92, p = 0.058, Cohen d = 0.75, 95% CI (-7.15 to 0.12)

pss

1st

t(100.38) = -1.37, p = 0.175, Cohen d = 0.50, 95% CI (-8.40 to 1.55)

2st

t(115.97) = -1.71, p = 0.091, Cohen d = 0.68, 95% CI (-10.04 to 0.75)

rki_responsible

1st

t(107.56) = 1.15, p = 0.254, Cohen d = -0.38, 95% CI (-0.70 to 2.63)

2st

t(121.58) = 0.59, p = 0.554, Cohen d = -0.22, 95% CI (-1.28 to 2.38)

rki_nonlinear

1st

t(102.19) = 0.76, p = 0.451, Cohen d = -0.27, 95% CI (-0.81 to 1.80)

2st

t(117.55) = 1.39, p = 0.168, Cohen d = -0.54, 95% CI (-0.42 to 2.41)

rki_peer

1st

t(104.45) = -0.26, p = 0.799, Cohen d = 0.09, 95% CI (-1.17 to 0.90)

2st

t(119.36) = 0.04, p = 0.970, Cohen d = -0.01, 95% CI (-1.11 to 1.15)

rki_expect

1st

t(124.74) = 1.83, p = 0.069, Cohen d = -0.49, 95% CI (-0.03 to 0.84)

2st

t(129.87) = 1.73, p = 0.085, Cohen d = -0.52, 95% CI (-0.06 to 0.92)

rki

1st

t(106.92) = 1.37, p = 0.175, Cohen d = -0.45, 95% CI (-0.78 to 4.24)

2st

t(121.15) = 1.41, p = 0.162, Cohen d = -0.52, 95% CI (-0.80 to 4.72)

raq_possible

1st

t(109.12) = -0.43, p = 0.666, Cohen d = 0.14, 95% CI (-1.01 to 0.65)

2st

t(122.59) = 1.09, p = 0.276, Cohen d = -0.39, 95% CI (-0.41 to 1.42)

raq_difficulty

1st

t(101.34) = -0.58, p = 0.564, Cohen d = 0.21, 95% CI (-0.85 to 0.47)

2st

t(116.82) = -0.02, p = 0.986, Cohen d = 0.01, 95% CI (-0.72 to 0.71)

raq

1st

t(101.39) = -0.53, p = 0.594, Cohen d = 0.19, 95% CI (-1.76 to 1.02)

2st

t(116.87) = 0.64, p = 0.522, Cohen d = -0.25, 95% CI (-1.02 to 2.00)

who

1st

t(93.12) = 0.21, p = 0.831, Cohen d = -0.09, 95% CI (-1.77 to 2.19)

2st

t(108.31) = 0.13, p = 0.894, Cohen d = -0.06, 95% CI (-1.97 to 2.25)

phq

1st

t(87.11) = -0.66, p = 0.510, Cohen d = 0.33, 95% CI (-2.12 to 1.06)

2st

t(100.01) = -0.60, p = 0.549, Cohen d = 0.32, 95% CI (-2.17 to 1.16)

gad

1st

t(93.67) = -0.46, p = 0.647, Cohen d = 0.19, 95% CI (-1.79 to 1.12)

2st

t(108.97) = -0.23, p = 0.817, Cohen d = 0.10, 95% CI (-1.73 to 1.37)

nb_pcs

1st

t(89.34) = -0.99, p = 0.327, Cohen d = 0.46, 95% CI (-5.14 to 1.73)

2st

t(103.32) = 0.37, p = 0.713, Cohen d = -0.18, 95% CI (-2.95 to 4.31)

nb_mcs

1st

t(99.24) = 0.58, p = 0.562, Cohen d = -0.22, 95% CI (-2.73 to 4.99)

2st

t(114.92) = 0.17, p = 0.866, Cohen d = -0.07, 95% CI (-3.82 to 4.53)

Within treatment group

sets

1st vs 2st

t(68.27) = -0.61, p = 0.541, Cohen d = 0.16, 95% CI (-1.14 to 0.60)

setv

1st vs 2st

t(65.23) = 0.41, p = 0.685, Cohen d = -0.11, 95% CI (-0.47 to 0.72)

maks

1st vs 2st

t(62.42) = 0.78, p = 0.436, Cohen d = -0.21, 95% CI (-0.67 to 1.53)

ibs

1st vs 2st

t(64.44) = 1.44, p = 0.154, Cohen d = -0.38, 95% CI (-0.20 to 1.21)

ers_e

1st vs 2st

t(62.81) = 0.06, p = 0.950, Cohen d = -0.02, 95% CI (-0.40 to 0.43)

ers_r

1st vs 2st

t(66.77) = 0.74, p = 0.459, Cohen d = -0.20, 95% CI (-0.35 to 0.77)

pss_pa

1st vs 2st

t(66.64) = -1.44, p = 0.154, Cohen d = 0.38, 95% CI (-3.02 to 0.48)

pss_ps

1st vs 2st

t(64.51) = -0.00, p = 0.996, Cohen d = 0.00, 95% CI (-2.49 to 2.48)

pss

1st vs 2st

t(64.20) = 0.69, p = 0.493, Cohen d = -0.18, 95% CI (-2.36 to 4.86)

rki_responsible

1st vs 2st

t(65.71) = -0.58, p = 0.565, Cohen d = 0.15, 95% CI (-1.73 to 0.95)

rki_nonlinear

1st vs 2st

t(64.58) = 0.37, p = 0.711, Cohen d = -0.10, 95% CI (-0.79 to 1.15)

rki_peer

1st vs 2st

t(65.06) = 0.44, p = 0.663, Cohen d = -0.12, 95% CI (-0.62 to 0.97)

rki_expect

1st vs 2st

t(69.60) = 0.95, p = 0.346, Cohen d = -0.25, 95% CI (-0.22 to 0.63)

rki

1st vs 2st

t(65.58) = 0.13, p = 0.899, Cohen d = -0.03, 95% CI (-1.88 to 2.13)

raq_possible

1st vs 2st

t(66.04) = 1.11, p = 0.270, Cohen d = -0.29, 95% CI (-0.30 to 1.06)

raq_difficulty

1st vs 2st

t(64.40) = 0.70, p = 0.489, Cohen d = -0.18, 95% CI (-0.32 to 0.66)

raq

1st vs 2st

t(64.41) = 1.13, p = 0.264, Cohen d = -0.30, 95% CI (-0.45 to 1.60)

who

1st vs 2st

t(62.63) = -0.49, p = 0.629, Cohen d = 0.13, 95% CI (-1.55 to 0.95)

phq

1st vs 2st

t(61.27) = 0.11, p = 0.916, Cohen d = -0.03, 95% CI (-0.80 to 0.89)

gad

1st vs 2st

t(62.75) = 0.69, p = 0.493, Cohen d = -0.18, 95% CI (-0.61 to 1.25)

nb_pcs

1st vs 2st

t(61.78) = 1.87, p = 0.066, Cohen d = -0.50, 95% CI (-0.13 to 3.81)

nb_mcs

1st vs 2st

t(63.96) = -0.69, p = 0.491, Cohen d = 0.18, 95% CI (-3.70 to 1.80)

Within control group

sets

1st vs 2st

t(64.14) = -0.80, p = 0.427, Cohen d = 0.19, 95% CI (-1.12 to 0.48)

setv

1st vs 2st

t(62.23) = 0.93, p = 0.357, Cohen d = -0.22, 95% CI (-0.29 to 0.80)

maks

1st vs 2st

t(60.55) = 0.09, p = 0.932, Cohen d = -0.02, 95% CI (-0.96 to 1.05)

ibs

1st vs 2st

t(61.75) = 0.59, p = 0.557, Cohen d = -0.14, 95% CI (-0.45 to 0.83)

ers_e

1st vs 2st

t(60.78) = -2.78, p = 0.007, Cohen d = 0.68, 95% CI (-0.90 to -0.15)

ers_r

1st vs 2st

t(63.18) = -0.60, p = 0.550, Cohen d = 0.15, 95% CI (-0.67 to 0.36)

pss_pa

1st vs 2st

t(63.10) = -1.61, p = 0.113, Cohen d = 0.39, 95% CI (-2.90 to 0.32)

pss_ps

1st vs 2st

t(61.79) = 1.02, p = 0.312, Cohen d = -0.25, 95% CI (-1.11 to 3.43)

pss

1st vs 2st

t(61.60) = 1.49, p = 0.141, Cohen d = -0.36, 95% CI (-0.84 to 5.77)

rki_responsible

1st vs 2st

t(62.52) = 0.04, p = 0.966, Cohen d = -0.01, 95% CI (-1.21 to 1.26)

rki_nonlinear

1st vs 2st

t(61.83) = -0.71, p = 0.483, Cohen d = 0.17, 95% CI (-1.21 to 0.58)

rki_peer

1st vs 2st

t(62.12) = 0.05, p = 0.957, Cohen d = -0.01, 95% CI (-0.71 to 0.75)

rki_expect

1st vs 2st

t(65.03) = 0.89, p = 0.375, Cohen d = -0.21, 95% CI (-0.22 to 0.57)

rki

1st vs 2st

t(62.44) = -0.11, p = 0.911, Cohen d = 0.03, 95% CI (-1.94 to 1.74)

raq_possible

1st vs 2st

t(62.73) = -0.98, p = 0.332, Cohen d = 0.24, 95% CI (-0.93 to 0.32)

raq_difficulty

1st vs 2st

t(61.73) = -0.08, p = 0.940, Cohen d = 0.02, 95% CI (-0.46 to 0.43)

raq

1st vs 2st

t(61.73) = -0.61, p = 0.544, Cohen d = 0.15, 95% CI (-1.22 to 0.65)

who

1st vs 2st

t(60.67) = -0.41, p = 0.685, Cohen d = 0.10, 95% CI (-1.37 to 0.91)

phq

1st vs 2st

t(59.88) = 0.06, p = 0.956, Cohen d = -0.01, 95% CI (-0.75 to 0.79)

gad

1st vs 2st

t(60.74) = 0.39, p = 0.697, Cohen d = -0.10, 95% CI (-0.68 to 1.01)

nb_pcs

1st vs 2st

t(60.17) = -0.60, p = 0.550, Cohen d = 0.15, 95% CI (-2.33 to 1.25)

nb_mcs

1st vs 2st

t(61.46) = -0.14, p = 0.888, Cohen d = 0.03, 95% CI (-2.69 to 2.34)

Plot